Median survival for patients diagnosed with advanced cirrhosis is around 2 years and quality of life is poor. Fewer than a quarter of such patients receive referrals to palliative care and advanced care plans are also rare. Existing research from abroad suggests that hepatology staff aren’t familiar with referral criteria and assume that palliative services become involved only at the very end of life.
 
 To try and reduce barriers to referral, clinicians at Royal Brisbane Hospital developed a model called Hepatocare. They adapted a palliative care referral algorithm to include cirrhosis specific markers and continuity of care between the teams was provided by a clinical nurse consultant. The model was piloted model in 30 consecutive patients to the liver clinic, and its impact was assessed on rate of referrals, incidence of unplanned admissions, length of patient stay and rates of polypharmacy.

Guests
Professor James O’Beirne FRCP FRACP (Sunshine Coast Hospital and Health Service; University of the Sunshine Coast)
Dr Richard Skoien MBBS FRACP (Royal Brisbane and Women’s Hospital; University of Queensland)
Dr Alison Kearney FRACP MRCP (Royal Brisbane and Women’s Hospital; University of Queensland)
Olivia Cullen (Royal Brisbane and Women’s Hospital)

Key Reference 

• Alison Kearney, Neha Tiwari, Olivia Cullen, Amy Legg, Ismail Arbi, Carol Douglas, Barbara Leggett, Mary Fenech, Joanne Mina, Paris Hoey, Richard Skoien. Improving palliative and supportive care in advanced cirrhosis: the HepatoCare model of integrated collaborative care. Intern Medicine Journal. 2023 Nov;53(11):1963-1971

Production
Produced by Mic Cavazzini DPhil. Music licenced from Epidemic Sound includes ‘After the Freak Show’ by Luella Gren and ‘The Cold Shoulder’ by Kylie Dailey. 

Editorial feedback kindly provided by RACP physicians Aidan Tan and David Arroyo.

Please visit the Pomegranate Health web page for a transcript and supporting references. Login to MyCPD to record listening and reading as a prefilled learning activity. Subscribe to new episode email alerts or search for ‘Pomegranate Health’ in Apple Podcasts, Spotify, Castbox or any podcasting app.

Semaglutide, branded as Ozempic or Wegovy, is an analogue of glucagon-like peptide 1 which has glucose-dependent effects on insulin secretion. In this episode we discuss how semaglutide performs as an antihyperglycaemic agent compared to previous GLP-1 analogues and the soon-to-be launched tirzepatide. This dual agonist also binds receptors to glucose-dependent insulinotropic polypeptide, GIP.

GLP-1 and GIP are incretin hormones, secreted after food intake and involved in regulating gastric motility and appetite. The analogue therapies have resulted in weight loss of 10 to 20 percent in trials on patients with obesity or other weight-related comorbidities. For various reasons, however, they remain unsubsidised by the Pharmaceutical Benefits Scheme. This hasn’t stopped social media influencers driving up off-label demand from the wider public, creating a problem for regulators and the diabetic patients most in need.

Guests
Professor Chris Rayner MBBS PhD FRACP (Gwendolyn Michell Professor, Adelaide Medical School; Consultant Gastroenterologist, Royal Adelaide Hospital)
Professor Gary Wittert MBBch, MD, FRACP (Mortlock Professor, Adelaide Medical School; Senior Consultant Endocrinologist, Royal Adelaide Hospital)

Production
Produced by Mic Cavazzini DPhil. Music courtesy of Free Music Archive includes ‘Mister S’ by Tortue Super Sonic. Music licenced from Epidemic Sound includes ‘Multicolor’ and ‘Flower Fountain’ by Chill Cole, ‘Blacklight’ by John B Lund, and ‘Habitual’ by Ava Low. Image by Ketut Subiyanto courtesy of Pexels. 

Editorial feedback kindly provided by RACP physicians Stephen Bacchi, Aidan Tan, David Arroyo, Joseph Lee, Jia-Wen Chong, Li-Zsa Tan, Fionnuala Fagan, Stella Sarlos and Marion Leighton.

Please visit the Pomegranate Health web page for a transcript and supporting references. Login to MyCPD to record listening and reading as a prefilled learning activity. Subscribe to new episode email alerts or search for ‘Pomegranate Health’ in Apple Podcasts, Spotify, Castbox or any podcasting app.

We’ve known for a decade that about 50 percent of doctors meet the criteria for burnout, and the figure is up to 70 percent among trainees. But organisations have been left to come up with their own solutions to this, the result being that many simply offer band aid solutions rather than systemic ones. Unforgiving work conditions pose a problem for both recruitment and retention of staff to the health workforce. The New Zealand Health Department, Te Whatu Ora, forecasts that within ten years supply of doctors, pharmacists and nurses will fall short of demand by 14 to 18 percent. In response they have establish they have established a national Health Charter that sets the workplace standards to keep staff safe and engaged.

Australia is one step behind, but in early September there was a leadership conference aimed at developing a similar wellbeing strategy nationally. It was envisaged that there would be Chief Wellness Officers at every major health service, reporting validated metrics about their workforce to a national taskforce. And as explained in the keynote presentation at the conference, at the organisational level there are different responses appropriate to the three main domains that influence staff wellbeing; these being personal resilience, professional culture and basic administrative efficiency. This podcast captures reflections from wellbeing champions at several different Australasian health jurisdictions.
 

Guests
Dr George Eskander MB DCH DRANZCOG FRACGP (Executive Area Director Clinical Services; North Metropolitan Health Service & Sir Charles Gairdner Osborne Park Hospital Care Group)
Dr Bethan Richards MB FRACP MMed MSportsMed (Head of Rheumatology, Chief Medical Wellness Officer, Royal Prince Alfred Hospital; Senior Clinical Lecturer, The University of Sydney)
Dr Joanna Sinclair MB FANZCA (Senior Medical Officer Wellbeing Lead, Counties Manukau Health) Victoria Hirst (Chief of Knowledge Networks, General Manager of Health Roundtable, Beamtree)
Associate Professor Anne Powell BPharm, MBBS, FRACP (Program Director of Physician Education, Alfred Health in Melbourne; Monash University)
Professor Jennifer Martin MBChB MA FRACP PhD GAICD (Chair of Clinical Pharmacology, University of Newcastle; John Hunter Hospital)


Production
Produced by Mic Cavazzini DPhil. Music licenced from Epidemic Sound includes ‘Kryptonite’ by Blue Steel and ‘Thyone’ by Ben Elson. Music courtesy of Free Music Archive includes ‘A Path Unwinding’ and ‘The Zepplin’ by Blue Dot Sessions and ‘Summer Days’ by Kai Engel. Image by sturti licenced from Getty Images. 

Editorial feedback kindly provided by physicians Aidan Tan and David Arroyo. Thanks also to Sarah Dalton and Fiona Fitzgerald for their coordination support.

Please visit the Pomegranate Health web page for a transcript and supporting references. Login to MyCPD to record listening and reading as a prefilled learning activity. Subscribe to new episode email alerts or search for ‘Pomegranate Health’ in 

This is the final episode in a five-part series about artificial intelligence in medicine. We start by weighing up the costs and benefits of automation in a health system that’s increasingly pushed beyond capacity. One of the biggest time sinks for health practitioners is filling out and searching through medical records. Some of this could be performed by natural language processors which are becoming more accurate thanks to deep learning. 
 
 The power of large language models has been demonstrated by the meteoritic uptake of ChatGPT and doctors are among those who have used it to summarise literature or draft letters. But professional organisations have raised concerns around the accuracy and privacy of the model and there have also been spooky demonstrations of its capacity for common sense and theory of mind. 

Guests
>Professor Brent Richards MBBS FRACP JJFICM (Gold Coast Hospital and Health Service; Director, IntelliHQ)
>Affiliate Associate Professor Paul Cooper PhD FAIDH CHIA AFHEA GAICD (Deakin University)
>Associate Professor Sandeep Reddy MBBS PhD IPFPH ECFMG CHIA FAcadTM FAIDH FCHSM SFHEA (Deakin University; Founder, MedAI)

Production
Produced by Mic Cavazzini DPhil. Music licenced from Epidemic Sound includes ‘Kryptonite’ by Blue Steel and ‘Thyone’ by Ben Elson. Music courtesy of Free Music Archive includes ‘Headway’ by Kai Engel, ‘Gramaphone’ by Jahzarr and ‘Numbers’ by Krowne. Image by VM licenced from Getty Images. Computerised voice from Online Tone Generator

Editorial feedback kindly provided by physicians David Arroyo, Stephen Bacchi, Aidan Tan, Ronaldo Piovezan and Rahul Barmanray and RACP staff Natasa Lazarevic PhD. 

Please visit the Pomegranate Health web page for a transcript and supporting references. Login to MyCPD to record listening and reading as a prefilled learning activity. Subscribe to new episode email alerts or search for ‘Pomegranate Health’ in Apple Podcasts, Spotify, Castbox or any podcasting app. 

This is the fourth part in a series on artificial intelligence in medicine and we try and unpick the causes and consequences of adverse events resulting from this technology. Our guest David Lyell is a research fellow at the Australian Institute of Health Innovation (Macquarie University) who has published a first-of-its kind audit of adverse events reported to the US regulator, the Federal Drugs Administration. He breaks down those that were caused by errors in the machine learning algorithm, other aspects of a device or even user error. 
 
We also discuss where these all fit in to the four stages of human information processing, and whether this can inform determinations about liability. Uncertainty around the medicolegal aspects of AI-assisted care is of the main reasons that practitioners report discomfort about the use of this technology. It's a question that hasn’t been well tested yet in the courts, though according to academic lawyer Rita Matulonyte, AI-enhanced devices don’t change the scope of care that has been expected of practitioners in the past. 

Guests
>Rita Matuolynte PhD (Macquarie Law School, Macquarie University; ARC Centre of Excellence for Automated Decision Making and Society; MQ Research Centre for Agency, Values and Ethics)
>David Lyell PhD (Australian Institute of Health Innovation, Macquarie University; owner Future Echoes Business Solutions)

Production
Produced by Mic Cavazzini DPhil. Music licenced from Epidemic Sound includes ‘Kryptonite’ by Blue Steel and ‘Illusory Motion’ by Gavin Luke. Music courtesy of Free Music Archive includes ‘Impulsing’ by Borrtex. Image by EMS-Forster-Productions licenced from Getty Images. 

Editorial feedback kindly provided by physicians David Arroyo, Stephen Bacchi, Aidan Tan, Ronaldo Piovezan and Rahul Barmanray and RACP staff Natasa Lazarevic PhD. 

Key References
More than algorithms: an analysis of safety events involving ML-enabled medical devices reported to the FDA [Lyell, J Am Med Inform Assoc. 2023]
How machine learning is embedded to support clinician decision making: an analysis of FDA-approved medical devices [Lyell, BMJ Health Care Inform. 2021]
Should AI-enabled medical devices be explainable? [Matulonyte, Int J Law Inform Tech. 2022]

Please visit the Pomegranate Health web page for a transcript and supporting references. Login to MyCPD to record listening and reading as a prefilled learning activity. Subscribe to new episode email alerts or search for ‘Pomegranate Health’ in Apple Podcasts, Spotify, Castbox or any podcasting app.

On the 28th of January 2022 a 75-year-old man was admitted to the regional Albury Wodonga Health Service with a high fever and Parkinsonian symptoms. The patient spent over a week in intensive care, but brain scans did not reveal an obvious aetiology and assays for a range of pathogens came up negative.

When serology eventually revealed the presence of antibodies against Japanese encephalitis virus this became only the second ever locally-acquired case on Australia’s mainland. Even more startling was the fact that the previous one had been way back in 1998 in Cape York, far north Queensland. 

The Victorian patient was the first what would become an outbreak of 43 symptomatic human cases that resulted in six deaths. The JE virus would be detected in all mainland states and retrospectively linked to another fatality in March 2021 from the Tiwi islands of the Northern Territory. In this podcast we hear about the confluence of factors that brought a classically tropical disease to the southern states. The story is told from the perspective of the treating clinicians, microbiology specialist and public health physician who started putting the puzzle together from four sentinel cases.

Key Reference

• Samuel Thorburn, Deborah Friedman, John Burston, Paul M Kinsella, Genevieve E Martin, Deborah Williamson, Justin Jackson. Sentinel cluster of locally acquired Japanese encephalitis in southern Australia. Internal Medicine Journal. 2023;53(5):835-840

Member access to Internal Medicine Journal, Journal of Paediatrics and Child Health and Occupational Medicine Journal

Guests
Adjunct Associate Professor Ian Woolley FRACP (Monash Infectious Diseases; Monash University)
Dr Justin Jackson FRACP (Albury Wodonga Health)
Dr Sam Thorburn (Austin Health)
Dr Paul Kinsella (Victorian Infectious Diseases Reference Laboratory, Peter Doherty Institute for Infection and Immunity)
Associate Professor Deborah Friedman FRACP (Victorian Department of Health; Deakin University)

Production
Produced by Mic Cavazzini DPhil. Music licenced from Epidemic Sound includes ‘Dusty Delta Day’ and ‘Hard Shoulder’ by Lennon Hutton. Editorial feedback kindly provided by Dr Aidan Tan. 

Please visit the Pomegranate Health web page for a transcript and supporting references. Login to MyCPD to record listening and reading as a prefilled learning activity. Subscribe to new episode email alerts or search for ‘Pomegranate Health’ in Apple Podcasts, Spotify,Castbox, or any podcasting app. 

This is the third part of a series on artificial intelligence in medicine. Previously we explained how to train and test machine learning models that assist in decision-making, and then how to iron out ergonomic friction points in the clinical workflow. We’ve mentioned how deep learning neural networks are more capable than classical models at dealing with big noisy data sets, but also that the reasoning they use to solve questions asked of them might be inexplainable users. 
 
This creates a certain unease among clinicians and regulators like Australia’s Therapeutic Goods Administration. According to some, we just need to test outcomes from use of AI-assisted decision-making with same rigor we do for pharmaceutical interventions, not all of which we fully understand. But despite updates to the SPIRIT and CONSORT for reporting of randomised controlled trials, there hasn’t yet been a lot of high quality clinical research into use of AI-based medical devices. 

Guests
>Affiliate Associate Professor Paul Cooper PhD FAIDH CHIA AFHEA GAICD (Deakin University)
>Associate Professor Sandeep Reddy MBBS PhD IPFPH ECFMG CHIA FAcadTM FAIDH FCHSM SFHEA (Deakin University)
>Professor Brent Richards MBBS FRACP JJFICM (Gold Coast Hospital and Health Service; Director, IntelliHQ)

Production
Produced by Mic Cavazzini DPhil. Music licenced from Epidemic Sound includes ‘Thyone’ by Ben Elson, ‘Little Liberty’ by Paisley Pink. Music courtesy of Free Music Archive includes ‘Impulsing’ and ‘You are not alone’ by Borrtex. Image by WestEnd61 licenced from Getty Images.

Editorial feedback kindly provided by physician Rahul Barmanray and digital health academic Natasa Lazarevic.

Key References
A governance model for the application of AI in health care [Reddy, J Am Med Inform Assoc. 2020]
Machine learning in clinical practice: prospects and pitfalls [Med J Aust. 2019]
Evidence-based medicine and machine learning: a partnership with a common purpose [BMJ Evid Based Med. 2021]
Explainability for artificial intelligence in healthcare: a multidisciplinary perspective [BMC Med Inform Decis Mak. 2020] 

Please visit the Pomegranate Health web page for a transcript and supporting references.Login to MyCPD to record listening and reading as a prefilled learning activity. Subscribe to new episode email alerts or search for ‘Pomegranate Health’ in Apple Podcasts, Spotify,Castbox, or any podcasting app.

The allure of having devices and tasks assisted by artificial intelligence is that they will help overcome some of the natural limits of human cognition with regards to working memory and attention. And in helping with the mundane tasks, AI can buy clinicians back time to spend with the complex patients who really need it. But the way all this pans out will really depend on how seamlessly the machine learning devices fit in with the clinical workflow. Which aspect of clinical decision-making do they support and how are the consequences of error mitigated? Only a small fraction of research projects make it all the way to implementation, and in this podcast we discuss the ergonomic factors that need to be solved to effectively use AI in clinical decision support.
 
Guests
Associate Professor Clair Sullivan MBBS FRACP FACHI FAIDH CHIA (Director, Queensland Digital Health Centre; University of Queensland)
Professor Enrico Coiera MBBS PhD FACMI, FACHI (Director, Centre for Health Informatics, Australian Institute of Health Innovation; Macquarie University).

Production
Produced by Mic Cavazzini DPhil. Music licenced from Epidemic Sound includes ‘Alienated’ by ELFL and ‘Little Liberty’ by Paisely Pink. Image by Da Kuk licenced from Getty Images.

Editorial feedback kindly provided by physicians; Rhiannon Mellor, David Arroyo, Aidan Tan, Joseph Lee, Rachel Murdoch, Michelle Chong, Phillipa Wormald and digital health academics; Paul Cooper and Natasa Lazarevic.

Key References
The Last Mile: Where Artificial Intelligence Meets Reality [Coiera, J Med Internet Res. 2019]
We need to chat about artificial intelligence [Coiera, MJA. 2023]
How machine learning is embedded to support clinician decision making: an analysis of FDA-approved medical devices [Coiera, BMJ Health Care Inform. 2021]

Please visit the Pomegranate Health web page for a transcript and supporting references. Login to MyCPD to record listening and reading as a prefilled learning activity. Subscribe to new episode email alerts or search for ‘Pomegranate Health’ in Apple Podcasts, Spotify, Castbox, or any podcasting app.

AI-assisted healthcare is reaching maturity in many applications and could alleviate some of the capacity gap increasingly faced by health systems . Over the next three podcasts we focus on artificial intelligence tools designed to assist directly with clinical practice. 

Most commonly reported on are the algorithms capable of pattern recognition on medical images, that in some settings perform as well or better than expert diagnosticians at classifying disease. AI models have also been developed to perform regression analyses more complex than classical risk stratification aids.

The standard statistical algorithms used to solve these problems struggle when many variables are introduced, in which case deep learning models that mimic brain networks are sometimes a powerful alternative. In this episode we explain how machine learning algorithms are trained on particular tasks and where there are risks of error and bias being introduced. 

In part 2, we identify the ergonomic issues that affect practical implementation of AI tools in the clinic and in the decision cascade. And in the final episode of the series we discuss the questions that regulators and lawyers should be asking of this new technology and what role natural language processors might have in medicine. 

Guest
Dr Ian Scott FRACP MHA MEd (Director of Internal Medicine and Clinical Epidemiology, Princess Alexandra Hospital; Professor of Medicine, University of Queensland)

Production
Produced by Mic Cavazzini DPhil. Music licenced from Epidemic Sound includes ‘Thyone’ by Ben Elson, ‘Broke No More’ by Cushy, ‘Desert Hideout’ by Christopher Moe Ditlevesen and ‘Alienated’ by ELFL. Music courtesy of Free Music Archive includes ‘Capgras’ by Ben Carey. Image by Olemedia licenced from Getty Images.

Editorial feedback kindly provided by physicians; Rhiannon Mellor, David Arroyo, Aidan Tan, Joseph Lee, Rachel Murdoch, Michelle Chong, Phillipa Wormald and digital health academics; Paul Cooper and Natasa Lazarevic.

Key References
Demystifying machine learning: a primer for physicians [Scott, IMJ. 2021]
Clinician checklist for assessing suitability of machine learning applications in healthcare [Scott, BMJ Health Care Inform. 2021]

Please visit the Pomegranate Health web page for a transcript and supporting references. Login to MyCPD to record listening and reading as a prefilled learning activity. Subscribe to new episode email alerts or search for ‘Pomegranate Health’ in Apple Podcasts, Spotify, Castbox, or any podcasting app.

In today’s podcast we try and understand the impact that racial bias makes on variation in clinical care. For example, racialized patterns in the use of analgesia were brought to light over 20 years ago but are still occurring today. In research from the UK published in March it was found that women of African or South Asian extraction were significantly less likely to receive an epidural during vaginal birth, or instrumental assistance with the delivery. The direct reasons for this variation were not revealed by the study, and could simply reflect the preferences of different cultural groups. But if that’s the case, it behoves us to address gaps in health education in a culturally sensitive way. 

This podcast highlights the subtle drivers of racialized disparity at different layers of service delivery. At an individual level implicit bias can affect clinical decision-making. At an institutional level there may be known resourcing issues not being addressed, like availability of translators to help diverse patients understand what they’re consenting to. And all this takes place within the context of structural racism, the inequity that was long ago baked into society’s power structures. That’s particularly true in colonised countries like ours, so we also ask what it means to “decolonise” medicine. 

Guests
Wendy Edmondson PhDc (Cultural Advisor, RACP)
Dr Kudzai Kanhutu FRACP GAICD MPH (Dean, RACP; Deputy Chief Information Office, Royal Melbourne Hospital)
 
Production
Produced by Mic Cavazzini DPhil. Recording assistance from Jon Tjhia in Melbourne and Fiona Croall in Adelaide.
 
Music licenced from Epidemic Sound includes ‘You break down’ by Czar Donic and ‘Repurposed’ by Cody Francis. Music courtesy of Free Music Archive includes ‘New Times’ by 4T Thieves and ‘Chasing Shadows’ by Scott Holmes. Image by rubberball licenced from Getty Images. 

Editorial feedback on this episode kindly provided by physicians Sern Wei Yeoh, Aidan Tan, Rachel Murdoch, Priya Garg, Fionnuala Fagan, Phillipa Wormald, Amy Hughes and RACP staff Fiona Hilton, Rebecca Lewis, Michele Daly, Alexandra Kinsey. 

Please visit the Pomegranate Health web page for a transcript and supporting references. Login to MyCPD to record listening and reading as a prefilled learning activity. Subscribe to new episode email alerts or search for ‘Pomegranate Health’ in Apple Podcasts, Spotify, Castbox, or any podcasting app.